Recursive least squares techniques applied to adaptive clutter filtering

The traditional approaches to clutter filtering lead to poor performance in the case of moving clutter such as weather. In an environment of severe nonstationary clutter and noise, an adaptive clutter filter is required which can adapt itself to the changing environment rapidly. This paper presents the application of two least-squares-type algorithms for adaptive clutter filtering and analyzes their performance.